Triple
T193571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Social Security Amendments of 1939 |
E3770
|
entity |
| Predicate | expandsCoverage |
P1673
|
FINISHED |
| Object | family members of insured workers |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: family members of insured workers | Statement: [Social Security Amendments of 1939, expandsCoverage, family members of insured workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expandsCoverage Context triple: [Social Security Amendments of 1939, expandsCoverage, family members of insured workers]
-
A.
expandedDuring
Indicates that an entity increased in size, scope, or extent over the course of a specified time period or event.
-
B.
extendsTo
chosen
Indicates that one entity reaches, stretches, or continues its scope, influence, or coverage up to or into another entity.
-
C.
mayExtendTo
Indicates that something has the potential or permission to reach, continue, or be applied up to a specified limit, scope, or boundary.
-
D.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
-
E.
spreadBy
Indicates that something is transmitted, dispersed, or propagated through the agency or action of a specified entity or medium.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2596810c48190ab687c0c2efaa9e2 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a256769ad8819083c1d83082c0215e |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.